For this dataset we use a simple “embedding-lookup” encoder, where each user and movie is associated with a unique embedding vector in \(\mathbb {R}^d\) .
As a scoring function, we follow [1]} and use a log-likelihood approach:
\(s(\langle u, r, m \rangle ) = \mathbf {z}_u^\top \mathbf {Q}_r\mathbf {z}_v-\log (\sum _{r^{\prime } \in \mathcal {R}}\mathbf {z}_u^\top \mathbf {Q}_{r^{\prime }}\mathbf {z}_v),\) 
